Van der Waals's energy models attraction and repulsion effects between pairs of atoms. This energy is used by ab initio methods to find the tertiary structure of a protein based only on its amino acid sequence and on a force field model. Several researches suggests Genetic Algorithms (GAs), are adequate for the development of ab initio approaches for protein structure prediction. A GA generates thousands of potential structures for a protein conformation, and evaluates the van der Waals' interaction in each generated structure. In practice, 99% of running time of the GA is used with the computation of van der Waals' energy. To compute the van der Waals energy for a given structure, we need to calculate effects of the interactions of all pairs of atoms in the structure. Using this cutoff, the complexity of the algorithm is O(n2) per conformation, where n is the number of atoms of the protein. For atoms separated by more than 8 Å the van der Waals effect is relatively weak. Thus, we apply a Cell-lists method to the van der Waals function reducing the complexity of algorithm to O(n). Furthermore, we applied parallel programming to the Cell-lists method using MPI, reducing significatively the running time. The combination of the Cell-lists and MPI techniques resulted in a speedup of 1000 for a protein with 147,900 atoms.